Within and between-person correlates of the temporal dynamics of resting EEG microstates

• Main Authors: Anthony P. Zanesco, Brandon G. King, Alea C. Skwara, Clifford D. Saron
• Format: Article
• Language: English
• Published: Elsevier 2020-05-01
• Series: NeuroImage
• Subjects: Aging; EEG; Individual differences; Markov-chain; Microstates; Mood
• Online Access: http://www.sciencedirect.com/science/article/pii/S105381192030118X

Microstates reflect transient brain states resulting from the synchronous activity of brain networks that predominate in the broadband EEG. There has been increasing interest in how the functional organization of the brain varies across individuals, or the extent to which its spatiotemporal dynamics are state dependent. However, little research has examined within and between-person correlates of microstate temporal parameters in healthy populations. In the present study, neuroelectric activity recorded during eyes-closed rest and during simple visual fixation was segmented into a time series of transient microstate intervals. It was found that five data-driven microstate configurations explained the preponderance of topographic variance in the EEG time series of the 374 recordings (from 187 participants) included in the study. We observed that the temporal dynamics of microstates varied within individuals to a greater degree than they differed between persons, with within-person factors explaining a large portion of the variance in mean microstate duration and occurrence rate. Nevertheless, several individual differences were found to predict the temporal dynamics of microstates. Of these, age and gender were the most reliable. These findings not only suggest that the rich temporal dynamics of whole-brain neuronal networks vary considerably within individuals, but that microstates appear to differentiate persons based on trait individual differences. Rather than focusing exclusively on between-person differences in microstates as measures of brain function, researchers should turn their attention towards understanding the factors contributing to within-person variation.